Product Feeds - ACP-Compliant AI Agent Discovery
Learn about ACP-compliant product feeds, automatic generation, feed formats (JSON, CSV, XML), optimization settings, and custom rules for AI agent discovery.
Product feeds are the foundation of agentic commerce, enabling AI agents to discover, understand, and recommend your products through natural conversation. GXO.dev automatically generates ACP-compliant feeds that optimize your products for AI agent discovery.
What are ACP-Compliant Product Feeds?
Agentic Commerce Protocol (ACP) Overview
The Agentic Commerce Protocol is a standardized format that enables AI agents to understand and interact with product data. ACP-compliant feeds ensure your products are:
- Discoverable: AI agents can find your products through natural language queries
- Understandable: Product information is structured for AI comprehension
- Actionable: AI agents can facilitate purchases and recommendations
- Optimized: Data is formatted for maximum AI agent effectiveness
Key Benefits of ACP Feeds
Enhanced AI Discovery
- Natural language product search
- Contextual product recommendations
- Intelligent product matching
- Conversational commerce experiences
Improved Performance
- Higher conversion rates from AI recommendations
- Better product visibility in AI interactions
- Optimized for AI agent understanding
- Real-time product updates
Standardized Format
- Consistent data structure across platforms
- Universal AI agent compatibility
- Future-proof product data
- Seamless integration with AI platforms
Automatic Feed Generation
How Automatic Generation Works
Data Synchronization
- Platform Connection: Connect your e-commerce platform (Shopify, Etsy, BigCommerce, Stripe)
- Product Sync: GXO.dev automatically syncs your product data
- ACP Transformation: Data is transformed into ACP-compliant format
- Feed Generation: Feeds are generated in multiple formats
- AI Publishing: Feeds are made available to AI agents
Real-Time Updates
- Inventory changes sync immediately
- Price updates reflect in real-time
- New products appear automatically
- Product modifications update instantly
Feed Generation Process
Step 1: Data Collection
- Collect product information from connected platforms
- Gather inventory and pricing data
- Retrieve product images and metadata
- Collect category and tag information
Step 2: Data Transformation
- Convert platform-specific data to ACP format
- Optimize product descriptions for AI
- Enhance product metadata
- Validate data quality and completeness
Step 3: Feed Creation
- Generate feeds in multiple formats (JSON, CSV, XML)
- Apply optimization rules and filters
- Create AI-friendly product descriptions
- Publish feeds for AI agent access
Step 4: AI Publishing
- Make feeds available to AI agents
- Enable natural language discovery
- Monitor AI agent interactions
- Track performance and optimization
Feed Formats and Options
JSON Format (Recommended)
Best for: AI agents, modern applications, real-time updates
Advantages:
- Native support in AI systems
- Real-time data updates
- Rich metadata support
- Easy parsing and processing
Structure:
{
"products": [
{
"id": "product_123",
"title": "Blue Cotton T-Shirt",
"description": "Comfortable blue cotton t-shirt...",
"price": 29.99,
"currency": "USD",
"availability": "in_stock",
"category": "Clothing > T-Shirts",
"images": ["https://example.com/image1.jpg"],
"attributes": {
"color": "Blue",
"size": "Medium",
"material": "Cotton"
}
}
]
}
CSV Format
Best for: Data analysis, bulk operations, compatibility
Advantages:
- Universal compatibility
- Easy to import and export
- Lightweight and fast
- Human-readable format
Structure:
id,title,description,price,currency,availability,category,image_url product_123,Blue Cotton T-Shirt,Comfortable blue cotton t-shirt...,29.99,USD,in_stock,Clothing > T-Shirts,https://example.com/image1.jpg
XML Format
Best for: Legacy systems, enterprise integration, structured data
Advantages:
- Structured data format
- Enterprise compatibility
- Rich metadata support
- Validation capabilities
Structure:
<products>
<product id="product_123">
<title>Blue Cotton T-Shirt</title>
<description>Comfortable blue cotton t-shirt...</description>
<price>29.99</price>
<currency>USD</currency>
<availability>in_stock</availability>
<category>Clothing > T-Shirts</category>
<image_url>https://example.com/image1.jpg</image_url>
</product>
</products>
Feed Optimization Settings
AI Optimization Features
Semantic Search Optimization
- Enhanced product descriptions for AI understanding
- Keyword optimization for natural language queries
- Context-aware product categorization
- AI-friendly product attributes
Image Analysis Integration
- Automatic image tagging and description
- Visual product recognition
- Color and style analysis
- AI-powered image optimization
Price Optimization
- Dynamic pricing strategies
- Competitive price analysis
- AI-driven price recommendations
- Market-based pricing adjustments
Custom Feed Rules
Product Filtering
- Include/exclude specific products
- Filter by price range or category
- Set minimum inventory levels
- Exclude discontinued items
Data Transformation
- Custom field mapping
- Description enhancement
- Category restructuring
- Attribute optimization
Quality Control
- Data validation rules
- Completeness checks
- Format standardization
- Error handling and reporting
Feed History and Versioning
Version Management
Automatic Versioning
- Each feed generation creates a new version
- Version history tracking
- Rollback capabilities
- Change comparison and analysis
Version Control
- Track changes between versions
- Compare feed performance
- Identify optimization opportunities
- Maintain feed stability
Feed Analytics
Performance Metrics
- AI agent interaction rates
- Product discovery frequency
- Conversion rates by product
- Feed performance trends
Optimization Insights
- Product performance analysis
- AI agent query patterns
- Conversion attribution
- Optimization recommendations
Scheduling and Automation
Sync Frequency Options
Real-Time Sync
- Immediate updates for critical changes
- Best for inventory and pricing
- Higher resource usage
- Maximum data freshness
Hourly Sync
- Regular updates for product information
- Balanced performance and freshness
- Suitable for most use cases
- Efficient resource usage
Daily Sync
- Bulk updates for large catalogs
- Lower resource usage
- Suitable for stable products
- Cost-effective option
Automation Features
Smart Sync Scheduling
- Automatic optimization of sync frequency
- Performance-based adjustments
- Resource usage monitoring
- Cost optimization
Event-Driven Updates
- Webhook-triggered sync
- Platform event integration
- Real-time change detection
- Immediate update processing
Custom Feed Rules (Pro+)
Rule Creation
Conditional Logic
- If-then-else rules
- Multiple condition support
- Nested rule structures
- Complex filtering logic
Data Transformation
- Field mapping and conversion
- Data formatting rules
- Value calculations
- Custom attribute generation
Rule Examples
Price-Based Filtering
IF price > 100 THEN include_in_feed = true IF price < 10 THEN include_in_feed = false
Category Optimization
IF category = "Clothing" THEN description = description + " - Fashion forward and trendy"
Inventory Management
IF stock_quantity < 5 THEN availability = "limited_stock"
Feed Testing and Validation
Testing Tools
Feed Validator
- ACP compliance checking
- Data quality validation
- Format verification
- Error detection and reporting
AI Agent Testing
- Test product discovery with AI agents
- Simulate natural language queries
- Verify recommendation accuracy
- Performance testing and optimization
Validation Process
Data Quality Checks
- Required field validation
- Data format verification
- Completeness assessment
- Accuracy verification
ACP Compliance
- Protocol compliance checking
- Standard format verification
- AI agent compatibility testing
- Performance optimization
Troubleshooting Feed Issues
Common Problems
Feed Generation Failed
- Check platform connection status
- Verify product data quality
- Review sync settings
- Check for API rate limits
Data Quality Issues
- Missing required fields
- Incorrect data formats
- Incomplete product information
- Image accessibility problems
Performance Issues
- Slow feed generation
- High resource usage
- API rate limit exceeded
- Sync timeout errors
Solutions
Data Quality Improvement
- Review and update product information
- Ensure all required fields are populated
- Optimize product descriptions
- Improve image quality and accessibility
Performance Optimization
- Adjust sync frequency
- Optimize feed rules
- Monitor resource usage
- Scale resources as needed
Best Practices
Feed Optimization
Product Data Quality
- Complete product information
- High-quality product images
- Detailed product descriptions
- Accurate pricing and inventory
AI-Friendly Content
- Natural language product descriptions
- Contextual product attributes
- Clear category classification
- Optimized product titles
Regular Monitoring
- Monitor feed performance
- Track AI agent interactions
- Analyze conversion rates
- Optimize based on insights
Maintenance
Regular Updates
- Keep product information current
- Update pricing and inventory
- Refresh product descriptions
- Monitor feed health
Performance Monitoring
- Track feed generation times
- Monitor AI agent interactions
- Analyze conversion metrics
- Optimize based on data
Next Steps
Now that you understand product feeds:
Support and Resources
Getting Help
- Documentation: Comprehensive guides for all features
- Support: Email support for all plans
- Community: Discord community for peer support
- Training: Video tutorials and webinars
ACP Resources
- ACP Specification: Agentic Commerce Protocol
- AI Agent Integration: OpenAI Developer Docs
- Best Practices: ACP Implementation Guide
- Community: ACP Discord Community
Create ACP-compliant product feeds that enable AI agents to discover and recommend your products through natural conversation.